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Updated: Jun 26, 2025

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

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Published on: February 2, 2019

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TrG2P:一种基于转移学习的工具,集成多特征数据,用于准确预测作物产量

Jinlong Li1, Dongfeng Zhang1, Feng Yang1

  • 1Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China.

Plant communications
|May 16, 2024
PubMed
概括

转移学习通过利用非产量特征显著提高了作物产量预测的准确性. 新的TrG2P框架增强了基因组选择 (GS) 模型,以获得更好的作物育种结果.

关键词:
农作物 农作物 农作物从基因型到表型的基因型多个特征的多个特征.转移学习转移学习收益率预测 收益率预测

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